Update app.py

app.py

@@ -72,14 +72,11 @@ MASK_DIR =  os.path.join(base,"Masks")
 
 CSV_LOG_PATH =  "image_log.csv"
 
-# Create directories
-def set_read_write_permissions(path):
-    os.chmod(path, stat.S_IRUSR | stat.S_IWUSR | stat.S_IRGRP | stat.S_IWGRP | stat.S_IROTH | stat.S_IWOTH)
 
 # Create directories with read and write permissions
 for directory in [UPLOAD_DIR, MASK_DIR]:
     os.makedirs(directory, exist_ok=True)
-    set_read_write_permissions(directory)
+
 
 
 
@@ -208,18 +205,18 @@ def upload_page():
             filepath = os.path.join(UPLOAD_DIR, filename)
             converted_filepath = os.path.join(UPLOAD_DIR, converted_filename)
             
-            with open(filepath, "wb") as f:
-                f.write(bytes_data)
+            # Save original file using cv2
+            nparr = np.frombuffer(bytes_data, np.uint8)
+            img = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
+            cv2.imwrite(filepath, img)
             
             if file_extension in ['.tiff', '.tif']:
                 st.info('Processing GeoTIFF image...')
                 rgb_image = read_pansharpened_rgb(filepath)
                 cv2.imwrite(converted_filepath, cv2.cvtColor(rgb_image, cv2.COLOR_RGB2BGR))
                 st.success(f'GeoTIFF converted to 8-bit image and saved as {converted_filename}')
-                img = Image.open(converted_filepath)
             else:
-                img = Image.open(filepath)
-                img.save(converted_filepath)
+                cv2.imwrite(converted_filepath, img)
             
             if os.path.exists(converted_filepath):
                 st.success(f"Image saved successfully: {converted_filepath}")
@@ -228,12 +225,15 @@ def upload_page():
             else:
                 st.error(f"Failed to save image: {converted_filepath}")
             
-            st.image(img, caption='Uploaded Image', use_column_width=True)
+            # Display image using PIL (as Streamlit's st.image works better with PIL)
+            pil_img = Image.open(converted_filepath)
+            st.image(pil_img, caption='Uploaded Image', use_column_width=True)
             st.success(f'Image processed and saved as {converted_filename}')
 
             st.session_state.filename = converted_filename
 
-            img_array = np.array(img)
+            # Use cv2 for further processing
+            img_array = cv2.imread(converted_filepath)
 
             if img_array.shape[0] > 650 or img_array.shape[1] > 650:
                 st.info('Large image detected. Using patch-based processing.')
@@ -242,7 +242,10 @@ def upload_page():
             else:
                 st.info('Small image detected. Processing whole image at once.')
                 with st.spinner('Analyzing image...'):
-                    img_transformed = transforms(img)
+                    # Convert to RGB for the model
+                    img_rgb = cv2.cvtColor(img_array, cv2.COLOR_BGR2RGB)
+                    img_pil = Image.fromarray(img_rgb)
+                    img_transformed = transforms(img_pil)
                     prediction = predict(img_transformed)
                     full_mask = (prediction > 0.5).astype(np.uint8) * 255
 
@@ -269,7 +272,6 @@ def upload_page():
             st.success('Image analyzed')
             st.session_state.page = 'result'
             st.rerun()
-
 def result_page():
     st.title('Analysis Result')